Dr. Jiaojiao Yu | Software Engineering | Best Scholar Award
Dr. Jiaojiao Yu is a researcher at the Hubei Key Laboratory of Digital Finance Innovation, Hubei University of Economics. She earned her Ph.D. from Wuhan University and specializes in software engineering, large language models, and digital finance. Her work focuses on leveraging advanced technologies to drive innovation and solve real-world challenges in the digital economy.
🎓 Education
- Jiaojiao Yu earned her Ph.D. from Wuhan University, a leading institution renowned for academic excellence and cutting-edge research. Her academic journey equipped her with a robust foundation in advanced research methodologies and innovative problem-solving approaches.
💼 Experience
- Jiaojiao Yu has been acknowledged for her contributions to digital finance and software engineering through awards that highlight her commitment to advancing these fields.
🏆 Honors and Awards
- Jiaojiao Yu has been acknowledged for her contributions to digital finance and software engineering through awards that highlight her commitment to advancing these fields.
🛠️ Skills and Certifications
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Dr. Yu possesses expertise in software engineering, data analysis, large language models, and digital finance. She is also skilled in research design and collaboration, enabling her to spearhead multidisciplinary initiatives effectively.
🔬 Research Focus
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Her primary research areas encompass software engineering, the application of large language models, and innovations in digital finance. She explores the intersection of these domains to address real-world challenges and contribute to the development of intelligent, efficient systems.
Conclusion
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Dr. Jiaojiao Yu is a commendable candidate for the Research for Best Scholar Award. Her contributions to emerging fields, combined with her collaborative potential and innovative mindset, align perfectly with the award’s objectives to recognize groundbreaking research. Her work not only advances theoretical understanding but also drives practical applications in digital finance, making her a worthy nominee.
📄Publications
- Detecting Self-Admitted Technical Debts via Prompt-Based Method in Issue-Tracking Systems
Authors: Yu, J., Tian, H., Li, R., Zuo, Q., Di, Y.
Journal: Electronics (Switzerland), 2024 - Federated Cross-View E-Commerce Recommendation Based on Feature Rescaling
Authors: Li, R., Shu, Y., Cao, Y., Yu, J., Zhang, W.
Journal: Scientific Reports, 2024 - Detecting Multi-Type Self-Admitted Technical Debt with Generative Adversarial Network-Based Neural Networks
Authors: Yu, J., Zhou, X., Liu, X., Xie, Z., Zhao, K.
Journal: Information and Software Technology, 2023 - Food Risk Entropy Model Based on Federated Learning
Authors: Yu, J., Chen, Y., Wang, Z., Liu, J., Huang, B.
Journal: Applied Sciences (Switzerland), 2022 - Exploiting Gated Graph Neural Network for Detecting and Explaining Self-Admitted Technical Debts
Authors: Yu, J., Zhao, K., Liu, J., Xu, Z., Wang, X.
Journal: Journal of Systems and Software, 2022